This is my first completed project on Dataquest. Took me a week to finish it.
I would highly appreciate any feedback concerning my code, clarity of data analysis and its representation through markdowns, as well as the integrity of the project in general.
Here is the URL link to the last screen of my project:
Exploring Ebay Car Sale Data | Dataquest
Guided+project+1±+Ebay+Car+Sales.ipynb (92.7 KB)
Click here to view the jupyter notebook file in a new tab
Welcome to the community and congratulations for having completed your first project on on Exploring Ebay Car Sales Data. Your introduction, the use of markdown cell, use of comments , the conclusion are so informative, great work indeed. I have noticed some unique approaches in some parts of your workings ,which has broaden my understanding. For example, while removing the outliers, you have successfully managed the whole task with the help of quantiles ,never imagined of that , thumbs up for this buddy!.
Below is an alternative of renaming the columns and will render the same output as yours, though it’s like time consuming by entering all the column names but I think it’s more readable.
autos= ['date_crawled', 'name', 'seller', 'offer_type', 'price', 'abtest',
'vehicle_type', 'registration_year', 'gearbox', 'power_ps', 'model',
'odometer', 'registration_month', 'fuel_type', 'brand',
'unrepaired_damage', 'ad_created', 'nr_of_pictures', 'postal_code',
autos.columns = autos
Otherwise to me ,everything looks nice and just wishing a happy learning!
Thank you very much for the feedback and the tip on column renaming! I’ll keep this tip in mind as it seems to be a bit easier way to rename them
here’s another alternative for converting camel to snake
res = [str.lower()]
for c in str[1:]:
if c in ('ABCDEFGHIJKLMNOPQRSTUVWXYZ'):
snake_headers = 
for row in all_headers:
snake = change_case(row)